{"id":"W4238845440","doi":"10.1016/j.jmir.2019.11.033","title":"Implementation of Single Alpha-Particle Traversal Microdosimetric Model","year":2019,"lang":"en","type":"article","venue":"Journal of medical imaging and radiation sciences","topic":"Radiation Therapy and Dosimetry","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Nuclear Laboratories","funders":"","keywords":"Dosimetry; Monte Carlo method; Tree traversal; Alpha particle; Physics; Computational fluid dynamics; Particle therapy; Computer science; Computational physics; Nuclear physics; Simulation; Mechanics; Nuclear medicine; Beam (structure); Algorithm; Mathematics; Medicine; Optics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001979472,0.0003848486,0.0004098973,0.0002677717,0.0002871874,0.000839858,0.001393142,0.0006040708,0.009773146],"category_scores_gemma":[0.0006503069,0.0003113463,0.0005494551,0.0002794274,0.000113248,0.0005202465,0.0005087672,0.0005625158,0.002385267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005189194,"about_ca_system_score_gemma":0.001060471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005771099,"about_ca_topic_score_gemma":0.004132643,"domain_scores_codex":[0.9998119,0.00002183639,0.00001046705,0.00003377277,0.00009794858,0.00002405891],"domain_scores_gemma":[0.9997383,0.00004443323,0.00001784186,0.00006427741,0.0001179495,0.000017137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003098,0.0001228509,0.003774254,0.0002015621,0.00008447951,0.0003098542,0.00019722,0.7825875,0.02414277,0.02219734,0.008541075,0.1575313],"study_design_scores_gemma":[0.00001614128,0.00002341916,0.0002802958,0.000006603365,0.0000109087,0.00007914601,0.00001590046,0.9775933,0.01128017,0.001833822,0.008849278,0.00001098695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02155818,0.00008756718,0.9599891,0.0001267995,0.00007071706,0.00008205772,0.0005329364,0.007873541,0.009679137],"genre_scores_gemma":[0.5686667,0.0002136344,0.4103745,0.0001273121,0.00002667359,0.0002005476,0.001528086,0.001560317,0.01730233],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009773146,"threshold_uncertainty_score":0.0326944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02123214537852571,"score_gpt":0.3513826249458261,"score_spread":0.3301504795673004,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}